{
 "cells": [
  {
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   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "  inflating: Images/airplane_617.jpg  \r\n"
     ]
    }
   ],
   "source": [
    "!unzip Images.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  Airplanes_Annotations.zip\r\n",
      "   creating: Airplanes_Annotations/\r\n",
      " extracting: Airplanes_Annotations/airplane_095.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_094.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_093.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_092.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_091.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_090.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_089.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_088.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_087.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_086.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_085.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_084.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_083.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_082.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_081.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_080.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_079.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_078.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_077.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_076.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_075.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_074.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_073.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_072.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_070.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_067.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_065.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_062.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_059.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_057.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_054.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_051.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_049.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_046.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_043.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_041.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_038.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_035.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_033.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_030.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_027.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_025.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_022.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_019.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_017.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_014.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_011.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_009.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_006.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_003.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_001.csv  \r\n",
      "  inflating: Airplanes_Annotations/hotanairport2-rgb.csv  \r\n",
      "  inflating: Airplanes_Annotations/42845.csv  \r\n",
      "  inflating: Airplanes_Annotations/42849.csv  \r\n",
      "  inflating: Airplanes_Annotations/428451.csv  \r\n",
      " extracting: Airplanes_Annotations/428452.csv  \r\n",
      "  inflating: Airplanes_Annotations/428461.csv  \r\n",
      " extracting: Airplanes_Annotations/428462.csv  \r\n",
      "  inflating: Airplanes_Annotations/428472.csv  \r\n",
      " extracting: Airplanes_Annotations/428481.csv  \r\n",
      "  inflating: Airplanes_Annotations/428482.csv  \r\n",
      "  inflating: Airplanes_Annotations/428483.csv  \r\n",
      "  inflating: Airplanes_Annotations/428491.csv  \r\n",
      " extracting: Airplanes_Annotations/428492.csv  \r\n",
      " extracting: Airplanes_Annotations/428501.csv  \r\n",
      " extracting: Airplanes_Annotations/428503.csv  \r\n",
      "  inflating: Airplanes_Annotations/planes2.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes1.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes4.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes9.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes3.csv  \r\n",
      " extracting: Airplanes_Annotations/Lhasa.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes7.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes11.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes10.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes6.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes8.csv  \r\n",
      "  inflating: Airplanes_Annotations/Planes12.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_071.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_069.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_068.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_066.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_064.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_063.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_061.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_060.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_058.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_056.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_055.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_053.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_052.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_050.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_048.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_047.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_045.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_044.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_042.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_040.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_039.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_037.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_036.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_034.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_032.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_031.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_029.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_028.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_026.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_024.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_023.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_021.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_020.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_018.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_016.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_015.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_013.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_012.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_010.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_008.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_007.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_005.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_004.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_002.csv  \r\n",
      "  inflating: Airplanes_Annotations/hotanairport5-rgb.csv  \r\n",
      "  inflating: Airplanes_Annotations/hotanairport5.csv  \r\n",
      "  inflating: Airplanes_Annotations/hotanairport1-rgb.csv  \r\n",
      " extracting: Airplanes_Annotations/42847.csv  \r\n",
      " extracting: Airplanes_Annotations/42848.csv  \r\n",
      "  inflating: Airplanes_Annotations/42850.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_223.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_222.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_221.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_220.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_219.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_218.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_217.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_216.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_215.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_214.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_213.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_212.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_211.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_210.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_209.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_208.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_207.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_206.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_205.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_204.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_203.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_202.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_201.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_200.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_199.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_198.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_197.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_196.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_195.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_194.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_193.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_192.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_191.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_190.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_189.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_188.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_187.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_186.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_185.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_184.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_183.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_182.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_181.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_180.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_179.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_178.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_177.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_176.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_175.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_174.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_173.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_172.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_171.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_170.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_169.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_168.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_167.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_166.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_165.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_164.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_163.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_162.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_161.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_160.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_159.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_158.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_157.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_156.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_155.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_154.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_153.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_152.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_151.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_150.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_149.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_148.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_147.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_146.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_145.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_144.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_143.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_142.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_141.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_140.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_139.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_138.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_137.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_136.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_135.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_134.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_133.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_132.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_131.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_130.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_129.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_128.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_127.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_126.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_125.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_124.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_123.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_122.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_121.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_120.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_119.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_118.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_117.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_116.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_115.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_114.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_113.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_112.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_111.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_110.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_109.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_108.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_107.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_106.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_105.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_104.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_103.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_102.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_101.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_100.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_099.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_098.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_097.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_096.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_351.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_350.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_349.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_348.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_347.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_346.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_345.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_344.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_343.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_342.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_341.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_340.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_339.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_338.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_337.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_336.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_335.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_334.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_333.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_332.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_331.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_330.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_329.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_328.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_327.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_326.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_325.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_324.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_323.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_322.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_321.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_320.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_319.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_318.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_317.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_316.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_315.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_314.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_313.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_312.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_311.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_310.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_309.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_308.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_307.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_306.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_305.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_304.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_303.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_302.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_301.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_300.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_299.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_298.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_297.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_296.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_295.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_294.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_293.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_292.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_291.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_290.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_289.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_288.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_287.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_286.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_285.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_284.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_283.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_282.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_281.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_280.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_279.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_278.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_277.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_276.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_275.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_274.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_273.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_272.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_271.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_270.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_269.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_268.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_267.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_266.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_265.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_264.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_263.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_262.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_261.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_260.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_259.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_258.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_257.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_256.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_255.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_254.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_253.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_252.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_251.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_250.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_249.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_248.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_247.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_246.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_245.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_244.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_243.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_242.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_241.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_240.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_239.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_238.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_237.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_236.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_235.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_234.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_233.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_232.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_231.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_230.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_229.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_228.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_227.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_226.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_225.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_224.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_479.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_478.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_477.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_476.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_475.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_474.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_473.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_472.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_471.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_470.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_469.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_468.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_467.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_466.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_465.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_464.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_463.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_462.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_461.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_460.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_459.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_458.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_457.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_456.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_455.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_454.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_453.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_452.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_451.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_450.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_449.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_448.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_447.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_446.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_445.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_444.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_443.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_442.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_441.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_440.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_439.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_438.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_437.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_436.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_435.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_434.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_433.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_432.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_431.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_430.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_429.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_428.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_427.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_426.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_425.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_424.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_423.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_422.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_421.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_420.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_419.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_418.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_417.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_416.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_415.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_414.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_413.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_412.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_411.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_410.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_409.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_408.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_407.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_406.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_405.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_404.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_403.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_402.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_401.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_400.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_399.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_398.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_397.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_396.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_395.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_394.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_393.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_392.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_391.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_390.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_389.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_388.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_387.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_386.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_385.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_384.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_383.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_382.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_381.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_380.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_379.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_378.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_377.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_376.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_375.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_374.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_373.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_372.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_371.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_370.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_369.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_368.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_367.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_366.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_365.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_364.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_363.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_362.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_361.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_360.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_359.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_358.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_357.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_356.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_355.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_354.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_353.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_352.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_607.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_606.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_605.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_604.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_603.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_602.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_601.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_600.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_599.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_598.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_597.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_596.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_595.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_594.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_593.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_592.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_591.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_590.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_589.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_588.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_587.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_586.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_585.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_584.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_583.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_582.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_581.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_580.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_579.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_578.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_577.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_576.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_575.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_574.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_573.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_572.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_571.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_570.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_569.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_568.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_567.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_566.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_565.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_564.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_563.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_562.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_561.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_560.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_559.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_558.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_557.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_556.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_555.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_554.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_553.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_552.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_551.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_550.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_549.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_548.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_547.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_546.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_545.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_544.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_543.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_542.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_541.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_540.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_539.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_538.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_537.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_536.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_535.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_534.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_533.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_532.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_531.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_530.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_529.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_528.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_527.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_526.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_525.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_524.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_523.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_522.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_521.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_520.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_519.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_518.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_517.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_516.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_515.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_514.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_513.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_512.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_511.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_510.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_509.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_508.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_507.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_506.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_505.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_504.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_503.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_502.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_501.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_500.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_499.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_498.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_497.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_496.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_495.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_494.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_493.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_492.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_491.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_490.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_489.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_488.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_487.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_486.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_485.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_484.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_483.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_482.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_481.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_480.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_700.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_699.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_698.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_697.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_696.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_695.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_694.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_693.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_692.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_691.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_690.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_689.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_688.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_687.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_686.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_685.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_684.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_683.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_682.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_681.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_680.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_679.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_678.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_677.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_676.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_675.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_674.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_673.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_672.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_671.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_670.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_669.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_668.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_667.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_666.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_665.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_664.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_663.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_662.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_661.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_660.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_659.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_658.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_657.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_656.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_655.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_654.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_653.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_652.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_651.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_650.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_649.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_648.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_647.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_646.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_645.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_644.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_643.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_642.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_641.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_640.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_639.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_638.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_637.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_636.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_635.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_634.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_633.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_632.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_631.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_630.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_629.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_628.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_627.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_626.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_625.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_624.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_623.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_622.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_621.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_620.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_619.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_618.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_617.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_616.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_615.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_614.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_613.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_612.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_611.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_610.csv  \r\n",
      "  inflating: Airplanes_Annotations/airplane_609.csv  \r\n",
      " extracting: Airplanes_Annotations/airplane_608.csv  \r\n"
     ]
    }
   ],
   "source": [
    "!unzip Airplanes_Annotations.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import os,cv2,keras\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"Images\"\n",
    "annot = \"Airplanes_Annotations\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "airplane_095.jpg\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for e,i in enumerate(os.listdir(annot)):\n",
    "    if e < 10:\n",
    "        filename = i.split(\".\")[0]+\".jpg\"\n",
    "        print(filename)\n",
    "        img = cv2.imread(os.path.join(path,filename))\n",
    "        df = pd.read_csv(os.path.join(annot,i))\n",
    "        plt.imshow(img)\n",
    "        for row in df.iterrows():\n",
    "            x1 = int(row[1][0].split(\" \")[0])\n",
    "            y1 = int(row[1][0].split(\" \")[1])\n",
    "            x2 = int(row[1][0].split(\" \")[2])\n",
    "            y2 = int(row[1][0].split(\" \")[3])\n",
    "            cv2.rectangle(img,(x1,y1),(x2,y2),(255,0,0), 2)\n",
    "        plt.figure()\n",
    "        plt.imshow(img)\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cv2.setUseOptimized(True);\n",
    "ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff519bfdc18>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "im = cv2.imread(os.path.join(path,\"42850.jpg\"))\n",
    "ss.setBaseImage(im)\n",
    "ss.switchToSelectiveSearchFast()\n",
    "rects = ss.process()\n",
    "imOut = im.copy()\n",
    "for i, rect in (enumerate(rects)):\n",
    "    x, y, w, h = rect\n",
    "#     print(x,y,w,h)\n",
    "#     imOut = imOut[x:x+w,y:y+h]\n",
    "    cv2.rectangle(imOut, (x, y), (x+w, y+h), (0, 255, 0), 1, cv2.LINE_AA)\n",
    "# plt.figure()\n",
    "plt.imshow(imOut)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_images=[]\n",
    "train_labels=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_iou(bb1, bb2):\n",
    "    assert bb1['x1'] < bb1['x2']\n",
    "    assert bb1['y1'] < bb1['y2']\n",
    "    assert bb2['x1'] < bb2['x2']\n",
    "    assert bb2['y1'] < bb2['y2']\n",
    "\n",
    "    x_left = max(bb1['x1'], bb2['x1'])\n",
    "    y_top = max(bb1['y1'], bb2['y1'])\n",
    "    x_right = min(bb1['x2'], bb2['x2'])\n",
    "    y_bottom = min(bb1['y2'], bb2['y2'])\n",
    "\n",
    "    if x_right < x_left or y_bottom < y_top:\n",
    "        return 0.0\n",
    "\n",
    "    intersection_area = (x_right - x_left) * (y_bottom - y_top)\n",
    "\n",
    "    bb1_area = (bb1['x2'] - bb1['x1']) * (bb1['y2'] - bb1['y1'])\n",
    "    bb2_area = (bb2['x2'] - bb2['x1']) * (bb2['y2'] - bb2['y1'])\n",
    "\n",
    "    iou = intersection_area / float(bb1_area + bb2_area - intersection_area)\n",
    "    assert iou >= 0.0\n",
    "    assert iou <= 1.0\n",
    "    return iou"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for e,i in enumerate(os.listdir(annot)):\n",
    "    try:\n",
    "        if i.startswith(\"airplane\"):\n",
    "            filename = i.split(\".\")[0]+\".jpg\"\n",
    "            print(e,filename)\n",
    "            image = cv2.imread(os.path.join(path,filename))\n",
    "            df = pd.read_csv(os.path.join(annot,i))\n",
    "            gtvalues=[]\n",
    "            for row in df.iterrows():\n",
    "                x1 = int(row[1][0].split(\" \")[0])\n",
    "                y1 = int(row[1][0].split(\" \")[1])\n",
    "                x2 = int(row[1][0].split(\" \")[2])\n",
    "                y2 = int(row[1][0].split(\" \")[3])\n",
    "                gtvalues.append({\"x1\":x1,\"x2\":x2,\"y1\":y1,\"y2\":y2})\n",
    "            ss.setBaseImage(image)\n",
    "            ss.switchToSelectiveSearchFast()\n",
    "            ssresults = ss.process()\n",
    "            imout = image.copy()\n",
    "            counter = 0\n",
    "            falsecounter = 0\n",
    "            flag = 0\n",
    "            fflag = 0\n",
    "            bflag = 0\n",
    "            for e,result in enumerate(ssresults):\n",
    "                if e < 2000 and flag == 0:\n",
    "                    for gtval in gtvalues:\n",
    "                        x,y,w,h = result\n",
    "                        iou = get_iou(gtval,{\"x1\":x,\"x2\":x+w,\"y1\":y,\"y2\":y+h})\n",
    "                        if counter < 30:\n",
    "                            if iou > 0.70:\n",
    "                                timage = imout[y:y+h,x:x+w]\n",
    "                                resized = cv2.resize(timage, (224,224), interpolation = cv2.INTER_AREA)\n",
    "                                train_images.append(resized)\n",
    "                                train_labels.append(1)\n",
    "                                counter += 1\n",
    "                        else :\n",
    "                            fflag =1\n",
    "                        if falsecounter <30:\n",
    "                            if iou < 0.3:\n",
    "                                timage = imout[y:y+h,x:x+w]\n",
    "                                resized = cv2.resize(timage, (224,224), interpolation = cv2.INTER_AREA)\n",
    "                                train_images.append(resized)\n",
    "                                train_labels.append(0)\n",
    "                                falsecounter += 1\n",
    "                        else :\n",
    "                            bflag = 1\n",
    "                    if fflag == 1 and bflag == 1:\n",
    "                        print(\"inside\")\n",
    "                        flag = 1\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        print(\"error in \"+filename)\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_new = np.array(train_images)\n",
    "y_new = np.array(train_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_new.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import Dense\n",
    "from keras import Model\n",
    "from keras import optimizers\n",
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras.applications.vgg16 import VGG16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vggmodel = VGG16(weights='imagenet', include_top=True)\n",
    "vggmodel.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for layers in (vggmodel.layers)[:15]:\n",
    "    print(layers)\n",
    "    layers.trainable = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X= vggmodel.layers[-2].output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = Dense(2, activation=\"softmax\")(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_final = Model(input = vggmodel.input, output = predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.optimizers import Adam\n",
    "opt = Adam(lr=0.0001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_final.compile(loss = keras.losses.categorical_crossentropy, optimizer = opt, metrics=[\"accuracy\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_final.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelBinarizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyLabelBinarizer(LabelBinarizer):\n",
    "    def transform(self, y):\n",
    "        Y = super().transform(y)\n",
    "        if self.y_type_ == 'binary':\n",
    "            return np.hstack((Y, 1-Y))\n",
    "        else:\n",
    "            return Y\n",
    "    def inverse_transform(self, Y, threshold=None):\n",
    "        if self.y_type_ == 'binary':\n",
    "            return super().inverse_transform(Y[:, 0], threshold)\n",
    "        else:\n",
    "            return super().inverse_transform(Y, threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lenc = MyLabelBinarizer()\n",
    "Y =  lenc.fit_transform(y_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test , y_train, y_test = train_test_split(X_new,Y,test_size=0.10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(X_train.shape,X_test.shape,y_train.shape,y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "trdata = ImageDataGenerator(horizontal_flip=True, vertical_flip=True, rotation_range=90)\n",
    "traindata = trdata.flow(x=X_train, y=y_train)\n",
    "tsdata = ImageDataGenerator(horizontal_flip=True, vertical_flip=True, rotation_range=90)\n",
    "testdata = tsdata.flow(x=X_test, y=y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.callbacks import ModelCheckpoint, EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint = ModelCheckpoint(\"ieeercnn_vgg16_1.h5\", monitor='val_loss', verbose=1, save_best_only=True, save_weights_only=False, mode='auto', period=1)\n",
    "early = EarlyStopping(monitor='val_loss', min_delta=0, patience=100, verbose=1, mode='auto')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist = model_final.fit_generator(generator= traindata, steps_per_epoch= 10, epochs= 1000, validation_data= testdata, validation_steps=2, callbacks=[checkpoint,early])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# plt.plot(hist.history[\"acc\"])\n",
    "# plt.plot(hist.history['val_acc'])\n",
    "plt.plot(hist.history['loss'])\n",
    "plt.plot(hist.history['val_loss'])\n",
    "plt.title(\"model loss\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.legend([\"Loss\",\"Validation Loss\"])\n",
    "plt.show()\n",
    "plt.savefig('chart loss.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "im = X_test[1600]\n",
    "plt.imshow(im)\n",
    "img = np.expand_dims(im, axis=0)\n",
    "out= model_final.predict(img)\n",
    "if out[0][0] > out[0][1]:\n",
    "    print(\"plane\")\n",
    "else:\n",
    "    print(\"not plane\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "z=0\n",
    "for e,i in enumerate(os.listdir(path)):\n",
    "    if i.startswith(\"4\"):\n",
    "        z += 1\n",
    "        img = cv2.imread(os.path.join(path,i))\n",
    "        ss.setBaseImage(img)\n",
    "        ss.switchToSelectiveSearchFast()\n",
    "        ssresults = ss.process()\n",
    "        imout = img.copy()\n",
    "        for e,result in enumerate(ssresults):\n",
    "            if e < 2000:\n",
    "                x,y,w,h = result\n",
    "                timage = imout[y:y+h,x:x+w]\n",
    "                resized = cv2.resize(timage, (224,224), interpolation = cv2.INTER_AREA)\n",
    "                img = np.expand_dims(resized, axis=0)\n",
    "                out= model_final.predict(img)\n",
    "                if out[0][0] > 0.65:\n",
    "                    cv2.rectangle(imout, (x, y), (x+w, y+h), (0, 255, 0), 1, cv2.LINE_AA)\n",
    "        plt.figure()\n",
    "        plt.imshow(imout)"
   ]
  }
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